The residual block for defining the ResNet backbone. Used in NCSNv2.

RefineBlock for building NCSNv2 RefineNet.

A residual block that can optionally change the number of channels. :param channels: the number of input channels. :param emb_channels:

A residual block that can optionally change the number of channels. :param channels: the number of input channels. :param emb_channels: t

A sequential module that passes timestep embeddings to the children that support it as an extra input.

A sequential module that passes timestep embeddings to the children that support it as an extra input.

Channel-wise self-attention block.

Channel-wise self-attention block.

An attention block that allows spatial positions to attend to each other. Originally ported from here, but adapted to the N-d case. http

An attention block that allows spatial positions to attend to each other. Originally ported from here, but adapted to the N-d case. https

A sequential module that passes timestep embeddings to the children that support it as an extra input.

Noise-conditional RefineBlock for building NCSNv1 RefineNet.

ConvMeanPool for building the ResNet backbone.

A downsampling layer with an optional convolution. :param channels: channels in the inputs and outputs. :param use_conv: a bool determin

A downsampling layer with an optional convolution. :param channels: channels in the inputs and outputs. :param use_conv: a bool determini

InceptionC block patched for FID computation

A residual block that can optionally change the number of channels. :param channels: the number of input channels. :param emb_channels:

An attention block that allows spatial positions to attend to each other. Originally ported from here, but adapted to the N-d case. http

`Large-scale CelebFaces Attributes (CelebA) Dataset <http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html>`_ Dataset. Args: root (string): Ro

InceptionA block patched for FID computation

`LSUN <https://www.yf.io/p/lsun>`_ dataset. Args: root (string): Root directory for the database files. classes (string or l

Transformer block for image-like data. First, project the input (aka embedding) and reshape to b, t, d. Then apply standard transform

An upsampling layer with an optional convolution. :param channels: channels in the inputs and outputs. :param use_conv: a bool determini

An upsampling layer with an optional convolution. :param channels: channels in the inputs and outputs. :param use_conv: a bool determinin

Defines a WideResnetGroup.

Maintains (exponential) moving average of a set of parameters.

An empty corrector that does nothing.

An empty predictor that does nothing.

A module which performs QKV attention and splits in a different order.

A module which performs QKV attention and splits in a different order.

Adapted from CLIP: https://github.com/openai/CLIP/blob/main/clip/model.py

Adapted from CLIP: https://github.com/openai/CLIP/blob/main/clip/model.py

Uses a pretrained BERT tokenizer by huggingface. Vocab size: 30522 (?)

A downsampling layer with an optional convolution. :param channels: channels in the inputs and outputs. :param use_conv: a bool determin

First InceptionE block patched for FID computation

Second InceptionE block patched for FID computation

Uses the CLIP transformer encoder for text (from Hugging Face)

Uses the CLIP transformer encoder for text.

Uses the CLIP image encoder.

Gaussian Fourier embeddings for noise levels.